In database design, what is the purpose of data normalization?

Data normalization is a systematic approach in database design aimed at reducing data redundancy and minimizing data anomalies. The primary objective of normalization is to organize the data within the database efficiently, ensuring that it adheres to certain rules, known as normal forms. This process involves breaking down larger tables into smaller, related tables and defining relationships between them.

By normalizing data, designers can achieve several benefits, including the prevention of data anomalies that can occur during data manipulation operations such as insertion, update, and deletion. For instance, without normalization, a database might have duplicate information across different tables, leading to inconsistencies and potential errors. By adhering to normalization principles, such as eliminating repeating groups and ensuring that each piece of data is stored in only one place, you can significantly reduce the risk of such anomalies, therefore maintaining data integrity and accuracy over time.

This process helps create a more efficient and manageable database structure that aligns with best practices in database management. While other options such as increasing redundancy or consolidating data into fewer tables might seem beneficial in certain contexts, they do not align with the core purpose of normalization, which is to promote data integrity and minimize anomalies. Enhancing user interfaces is also outside the scope of normalization, as it pertains more to front-end design rather